Status of the NEAMS and ARC neutronic fast reactor tools integration to the NEAMS Workbench

Stauff, Nicolas; Lartaud, P.; Jung, Yeon Sang; Lee, C. H.; Zeng, Kaiyue; Hou, Jason

doi:10.2172/1570009

Cited by 7 publications

(8 citation statements)

References 14 publications

(15 reference statements)

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“…Preliminary results show a difference of 950 pcm in eigenvalues between conventional and improved methods. Further verification of the improved cross section method will be performed with Serpent and NEAMS Workbench/PyARC [27] in the future work.…”

Section: Discussionmentioning

confidence: 99%

Nuclear Data Uncertainty Quantification and Propagation for Safety Analysis of Lead-Cooled Fast Reactors

Trivedi

Hou

Grasso

et al. 2020

Science and Technology of Nuclear Installations

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In this study, the Best Estimate Plus Uncertainty (BEPU) approach is developed for the systematic quantification and propagation of uncertainties in the modelling and simulation of lead-cooled fast reactors (LFRs) and applied to the demonstration LFR (DLFR) initially investigated by Westinghouse. The impact of nuclear data uncertainties based on ENDF/B-VII.0 covariances is quantified on lattice level using the generalized perturbation theory implemented with the Monte Carlo code Serpent and the deterministic code PERSENT of the Argonne Reactor Computational (ARC) suite. The quantities of interest are the main eigenvalue and selected reactivity coefficients such as Doppler, radial expansion, and fuel/clad/coolant density coefficients. These uncertainties are then propagated through safety analysis, carried out using the MiniSAS code, following the stochastic sampling approach in DAKOTA. An unprotected transient overpower (UTOP) scenario is considered to assess the effect of input uncertainties on safety parameters such as peak fuel and clad temperatures. It is found that in steady state, the multiplication factor shows the most sensitivity to perturbations in 235U fission, 235U ν, and 238U capture cross sections. The uncertainties of 239Pu and 238U capture cross sections become more significant as the fuel is irradiated. The covariance of various reactivity feedback coefficients is constructed by tracing back to common uncertainty contributors (i.e., nuclide-reaction pairs), including 238U inelastic, 238U capture, and 239Pu capture cross sections. It is also observed that nuclear data uncertainty propagates to uncertainty on peak clad and fuel temperatures of 28.5 K and 70.0 K, respectively. Such uncertainties do not impose per se threat to the integrity of the fuel rod; however, they sum to other sources of uncertainties in verifying the compliance of the assumed safety margins, suggesting the developed BEPU method necessary to provide one of the required insights on the impact of uncertainties on core safety characteristics.

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Section: Discussionmentioning

confidence: 99%

Nuclear Data Uncertainty Quantification and Propagation for Safety Analysis of Lead-Cooled Fast Reactors

Trivedi

Hou

Grasso

et al. 2020

Science and Technology of Nuclear Installations

Self Cite

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“…For conventional hexagonal and Cartesian geometry problems, the Argonne mesh toolkit is able to easily generate meshes with text-type keyword inputs. Recently, the NEAMS Workbench [23] has been updated with PyPROTEUS [24] which help users create PROTEUS inputs, run the code, and post-process code outputs.…”

Section: Proteusmentioning

confidence: 99%

Development of the PROTEUS and ANSYS Coupled System for Simulating Heat Pipe Cooled Micro Reactors

Lee

Jung

2020

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The objective of this project is to develop the coupled system of PROTEUS/ANSYS for simulating a heat pipe cooled micro reactor. As an initial effort, while figuring out controlling ANSYS Mechanical with Workbench, the coupled system of PROTEUS/FLUENT in the CORBA environment were tried to demonstrate the coupled simulation for a transient problem of a heat pipe cooled micro reactor. Finally, the coupled system of PROTEUS/ANSYS was constructed using APDL commands in the CORBA environment, instead of ANSYS Workbench, since we found that ANSYS with the current version of Workbench Python scripting did not provide capabilities necessary for simulating a transient problem.

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“…The NEAMS Workbench [4,14] initiative is designed to facilitate the transition from conventional design tools to more advanced modeling and simulation tools by providing a common user interface for model creation, review, execution, and visualization on personal computers and high-performance computing (HPC) platforms.…”

Section: Introductionmentioning

confidence: 99%

Documentation on How to Run the NEAMS Workbench GUI on Sawtooth

Delchini¹,

Lefebvre²

2022

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This document provides guidelines on how to run MOOSE-based applications from the NEAMS Workbench GUI on the HPC platform Sawtooth located at Idaho National Laboratory. The different steps are illustrated with a multi-app example modeling a sodium-cooled fast reactor (SFR) taken from the virtual test bed (VTB) website. The workflow consists of four steps to demonstrate the capabilities of the NEAMS Workbench GUI, that covers log into Sawtooth, editing and validating input files, submission of the job to the queue and visualization of the numerical solution and the geometry. Each step is illustrated with figures in the text, and a demonstration video is also available.

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Status of the NEAMS and ARC neutronic fast reactor tools integration to the NEAMS Workbench

Cited by 7 publications

References 14 publications

Nuclear Data Uncertainty Quantification and Propagation for Safety Analysis of Lead-Cooled Fast Reactors

Nuclear Data Uncertainty Quantification and Propagation for Safety Analysis of Lead-Cooled Fast Reactors

Development of the PROTEUS and ANSYS Coupled System for Simulating Heat Pipe Cooled Micro Reactors

Documentation on How to Run the NEAMS Workbench GUI on Sawtooth

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